Enhancing the Locality and Breaking the Memory Bottleneck of Transformer on Time Series Forecasting. - Shiyang Li; Xiaoyong Jin; Yao Xuan; Xiyou Zhou; Wenhu Chen; Yu-Xiang Wang 003; Xifeng Yan (NeurIPS, 2019)

Optimal Policies for a Pandemic: A Stochastic Game Approach and a Deep Learning Algorithm. - Yao Xuan; Robert Balkin; Jiequn Han; Ruimeng Hu; Héctor D. Ceniceros (MSML, 2021)

Deep learning and self-consistent field theory: A path towards accelerating polymer phase discovery. - Yao Xuan; Kris T. Delaney; Héctor D. Ceniceros; Glenn H. Fredrickson (J. Comput. Phys., 2021)

Sphere2Vec: Multi-Scale Representation Learning over a Spherical Surface for Geospatial Predictions. - Gengchen Mai; Yao Xuan; Wenyun Zuo; Krzysztof Janowicz; Ni Lao (CoRR, 2022)

Pandemic Control, Game Theory and Machine Learning. - Yao Xuan; Robert Balkin; Jiequn Han; Ruimeng Hu; Héctor D. Ceniceros (CoRR, 2022)

Machine Learning and Polymer Self-Consistent Field Theory in Two Spatial Dimensions. - Yao Xuan; Kris T. Delaney; Héctor D. Ceniceros; Glenn H. Fredrickson (CoRR, 2022)

Sphere2Vec: A General-Purpose Location Representation Learning over a Spherical Surface for Large-Scale Geospatial Predictions. - Gengchen Mai; Yao Xuan; Wenyun Zuo; Yutong He; Jiaming Song; Stefano Ermon; Krzysztof Janowicz; Ni Lao (CoRR, 2023)

Towards general-purpose representation learning of polygonal geometries. - Gengchen Mai; Chiyu Jiang 001; Weiwei Sun; Rui Zhu 008; Yao Xuan; Ling Cai; Krzysztof Janowicz; Stefano Ermon; Ni Lao (GeoInformatica, 2023)

A roadmap for T cell receptor-peptide-bound major histocompatibility complex binding prediction by machine learning: glimpse and foresight. - Furong Qi; Qiang Huang; Yao Xuan; Yingyin Cao; Yunyun Shen; Yihan Ren; Zhe Liu; Zheng Zhang (Briefings Bioinform., 2025)

Quantum-Boosted High-Fidelity Deep Learning. - Feng-ao Wang; Shaobo Chen; Yao Xuan; Junwei Liu; Qi Gao; Hongdong Zhu; Junjie Hou; Lixin Yuan; Jinyu Cheng; Chenxin Yi; Hai Wei; Yin Ma; et al. (CoRR, 2025)